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Full-Text Articles in Social and Behavioral Sciences
Modelling Dynamic Conditional Correlations In Wti Oil Forward And Futures Returns, Alessandro Lanza, Matteo Manera, Micheal Mcaleer
Modelling Dynamic Conditional Correlations In Wti Oil Forward And Futures Returns, Alessandro Lanza, Matteo Manera, Micheal Mcaleer
Matteo Manera
This paper estimates the dynamic conditional correlations in the returns on WTI oil onemonth forward prices, and one-, three-, six-, and twelve-month futures prices, using recently developed multivariate conditional volatility models. The dynamic correlations enable a determination of whether the forward and various futures returns are substitutes or complements, which are crucial for deciding whether or not to hedge against unforeseen circumstances. The models are estimated using daily data on WTI oil forward and futures prices, and their associated returns, from 3 January 1985 to 16 January 2004. At the univariate level, the estimates are statistically significant, with the occasional …
Long-Run Models Of Oil Stock Prices, Alessandro Lanza, Matteo Manera, Massimo Giovannini, Margherita Grasso
Long-Run Models Of Oil Stock Prices, Alessandro Lanza, Matteo Manera, Massimo Giovannini, Margherita Grasso
Matteo Manera
The identification of the forces that drive oil stock prices is extremely important given the size of the Oil&Gas industry and its links with the energy sector and the environment. In the next decade oil companies will have to deal with international policies to contrast climate change. This issue is likely to affect companies’ shareholder values. In this paper we focus on the long-run financial determinants of the stock prices of six major oil companies (Bp, Chevron-Texaco, Eni, Exxon-Mobil, Royal Dutch Shell, Total-Fina-Elf) using multivariate cointegration techniques and vector error correction models. Weekly oil stock prices are analyzed together with …
Forecasting Volatility In European Stock Markets With Non-Linear Garch Models, Giancarlo Forte, Matteo Manera
Forecasting Volatility In European Stock Markets With Non-Linear Garch Models, Giancarlo Forte, Matteo Manera
Matteo Manera
This paper investigates the forecasting performance of three popular variants of the nonlinear GARCH models, namely VS-GARCH, GJR-GARCH and Q-GARCH, with the symmetric GARCH(1,1) model as a benchmark. The application involves ten European stock price indexes. Forecasts produced by each non-linear GARCH model and each index are evaluated using a common set of classical criteria, as well as forecast combination techniques with constant and non-constant weights. With respect to the standard GARCH specification, the non-linear models generally lead to better forecasts in terms of both smaller forecast errors and lower biases. In-sample forecast combination regressions are better than those from …